from sklearn.model_selection import train_test_split
from crf_model import load_model
from data_processing import DataProcessor


max_len = 80
vocab_size = 6000
data = DataProcessor(max_len,vocab_size)
train_x, trainy,test_x, testy = data.read_data()

train_x, trainy = data.encoder(train_x,trainy)

x_train, x_dev, y_train, y_dev = train_test_split(train_x, trainy, test_size=0.25)

test_x, testy = data.encoder(test_x,testy)

crf_model = load_model()

crf_model.fit(X=train_x,y=trainy)

